A majority of electronic imaging devices are now implemented using semiconductor technologies. Examples include the charge coupled display (CCD), which is implemented using a MOS manufacturing process, and, more recently, image sensors manufactured using standard CMOS semiconductor processes. In all of these cases, the sensor normally includes a one or two dimensional array of discrete pixels. As a result of the manufacturing processes employed in the production of such devices, occasional defects occur at individual pixel sites. Such defects may cause the affected pixel to be brighter or darker than the true image at that point, including the extreme cases of saturated white or black pixels.
These defects affect some proportion of the plurality of individual imaging devices or chips on each manufactured wafer. The chips affected must normally be rejected unless the defects can be masked or corrected. It is more economical to mask or correct defective pixels, thus enabling otherwise rejected chips to be passed. This improves the apparent yield of good imaging chips per wafer, and, thereby lowers the cost per usable chip. It is known in the art to calibrate imaging devices at the point of camera manufacture so that the locations of defective pixels in the imaging array are identified and stored. In subsequent use of the device, pixel data from these locations are masked or corrected in the live video data stream.
One simple and well known masking technique is to substitute the defective data with a copy of the value of a neighboring or adjacent pixel. More sophisticated techniques are also possible, and typically may produce an estimate of the correct value of the defective pixel data. This is done by applying an algorithm to the data obtained from the neighboring pixels in one or two dimensions. Generally, the best correction filters use a mixture of linear and non-linear estimators and work on at least a 3×3 pixel neighborhood centered on the defective pixel.
This prior technique of calibrating individual sensors at the point of manufacture has two main disadvantages. First, and most significantly, the process of calibrating the sensor to determine defect locations is an inconvenient and expensive manufacturing burden. Second, defects may sometimes be transient in nature, so that defects present and corrected for at the time of calibration may subsequently disappear, or worse, new defects may occur subsequent to calibration. These latter defects will remain uncorrected in subsequent camera use and will result in blemishes on the images output by the camera.